By Topic

Impact on Image Noise of Incorporating Detector Blurring Into Image Reconstruction for a Small Animal PET Scanner

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Kisung Lee ; Dept. of Radiologic Sci., Korea Univ., Seoul, South Korea ; Robert S. Miyaoka ; Tom K. Lewellen ; Adam M. Alessio
more authors

We study the noise characteristics of an image reconstruction algorithm that incorporates a model of the non-stationary detector blurring (DB) for a mouse-imaging positron emission tomography (PET) scanner. The algorithm uses ordered subsets expectation maximization (OSEM) image reconstruction, which is used to suppress statistical noise. Including the non-stationary detector blurring in the reconstruction process [OSEM(DB)] has been shown to increase contrast in images reconstructed from measured data acquired on the fully-3D MiCES PET scanner developed at the University of Washington. As an extension, this study uses simulation studies with a fully-3D acquisition mode and our proposed FORE+ OSEM(DB) reconstruction process to evaluate the volumetric contrast versus noise trade-offs of this approach. Multiple realizations were simulated to estimate the true noise properties of the algorithm. The results show that incorporation of detector blurring FORE+OSEM(DB) into the reconstruction process improves the contrast/noise trade-offs compared to FORE +OSEM in a radially dependent manner. Adding post reconstruction 3D Gaussian smoothing to FORE +OSEM and FORE +OSEM(DB) reduces the contrast versus noise advantages of FORE+ OSEM(DB).

Published in:

IEEE Transactions on Nuclear Science  (Volume:56 ,  Issue: 5 )